Triple

T8015305
Position Surface form Disambiguated ID Type / Status
Subject Giresun E186597 entity
Predicate hasMunicipalGovernment P3291 FINISHED
Object Giresun Municipality E656516 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Giresun Municipality | Statement: [Giresun, hasMunicipalGovernment, Giresun Municipality]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Giresun Municipality
Context triple: [Giresun, hasMunicipalGovernment, Giresun Municipality]
  • A. Giresun, Turkey
    Giresun, Turkey is a Black Sea coastal city in northeastern Turkey known for its hazelnut production and lush, hilly landscape.
  • B. Giresun chosen
    Giresun is a coastal city in northeastern Turkey known for its hazelnut production and scenic location along the Black Sea.
  • C. Adalar Municipality
    Adalar Municipality is the local government authority responsible for administering public services and urban management on Istanbul’s Princes’ Islands district.
  • D. Galatsi municipality
    Galatsi municipality is a suburban residential area and local government unit within the Athens metropolitan region of Greece.
  • E. Chora District
    Chora District is an administrative district located within Afghanistan’s central Uruzgan Province.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ca82ac7fc081909b1398cf025423af completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3df24e4c8190ae1c46e97e54787d completed March 31, 2026, 3:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc56ba88b88190ad279d79d7f0ffd7 completed March 31, 2026, 11:20 p.m.
Created at: March 30, 2026, 5:20 p.m.